Biology subjects

Phillips, M. L.

Publications and source records attributed to Phillips, M. L..

12 recordsLinked to original sources

bioRxiv2026

Structural Brain Network Alterations in Relation to Treatment and Illness Severity in Bipolar Disorder

BackgroundLarge-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics. MethodsCross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7{+/-}12.6 years) and 510 controls (33.3{+/-}12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications. ResultsBD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged. ConclusionsAs the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

neuroscience↗

bioRxiv2025

A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty

To behave adaptively, people need to integrate information about probabilistic outcomes and balance drives to approach positive outcomes and avoid negative outcomes. However, questions remain about how uncertainty in positive and negative outcomes influence approach-avoid decision-making dynamics. To fill this gap, we developed a novel Probabilistic Approach Avoidance Task (PAAT) and characterized behavior in this task using sequential sampling models In this task, participants (Study 1: blinded mixed clinical sample N=34; Study 2: online nonpsychiatric sample N = 58) made a series of choices between pairs of options, each consisting of variable probabilities of reaching a positive outcome (monetary reward) and of reaching a negative outcome (aversive image). Participants tended to choose options that maximized the likelihood of reward and minimized the likelihood of aversive outcomes. Moreover, the weights they placed on each of these differed for choices where these likelihoods were in opposition (i.e., the riskier option was also more rewarding; incongruent trials) relative to when these were aligned (congruent trials). Computational modeling revealed that the relative influence of rewarding and aversive outcomes on choice was captured by differences in the rate of decision-relevant information accumulation. These modeling results were validated with a series of model comparisons and posterior predictive checks, demonstrating that our sequential sampling models reliably captured our behavioral data. Together, these findings improve our understanding of the influence of motivational conflict, outcome type, and levels of uncertainty on approach-avoid decision-making.

neuroscience↗

bioRxiv2025

Longitudinal Stability of Mood-Related Resting-State Networks in Youth with Symptomatic Bipolar-I/II Disorder

Bipolar disorder (BD) is characterized by temporal instability of mood and energy, but the neural correlates of this instability are poorly understood. In previous cross-sectional studies, mood state in BD has been associated with differential functional connectivity (FC) amongst several subcortical regions and ventromedial prefrontal cortex. Here, we assess whether BD is associated with longitudinal instability within this mood-related network of interest (NOI). Young people with BD-I/II were scanned 4-6 times and healthy controls (HC) were scanned 4 times over 9 months. Following preprocessing of 20-minute resting-state scans, we assessed across-scan correlation of FC, focusing on FC between regions previously associated with BD mood state. Utilizing Bayesian models, we assessed the relationship between diagnostic group and within-person, across-scan correlation, adjusting for motion, time-of-day, and inter-scan interval; prediction intervals (PI) are reported. In a sample of 16 youth (11 BD, 5 HC; 16.3-23.3 years old) with 70 scans (50 BD, 20 HC), across-scan NOI stability was higher within-than between-person (0.70 vs. 0.54; p<.0001). BD (vs. HC) within-person scan-pairs showed lower NOI stability (mean -0.109; 95% PI -0.181, -0.038), distinguishing BD vs. HC with excellent accuracy (AUC=0.95). NOI instability was more pronounced with manic symptoms (mean -0.012; 95% PI -0.023, -0.0002) and in BD-II (vs. BD-I; mean -0.071; 90% PI -0.136, -0.007). Results persisted after accounting for medications, comorbidity, and sleep/arousal measures. Within this pilot sample, BD is characterized by less within-person stability of a mood-related NOI. While preliminary, these results highlight a possible role for precision imaging approaches to elucidate neural mechanisms underlying BD.

neuroscience↗

bioRxiv2023

Functional imaging of nine distinct neuronal populations under a miniscope in freely behaving animals

Head-mounted miniscopes have enabled functional fluorescence imaging in freely moving animals. However, current technology is limited to recording at most two spectrally distinct fluorophores, severely restricting the number of identifiable cell types. Here we introduce multiplexed neuronal imaging (Neuroplex), a pipeline combining miniscope Ca2+ recordings with in vivo multiplexed confocal spectral imaging to distinguish nine projection-defined neuronal subtypes through the same GRIN lens. By co-registering defined neurons with fluorophore-specific spectral fingerprints via linear unmixing, we link projection-defined identities to behaviorally relevant neuronal activity. This approach overcomes spectral constraints of miniscopes, enabling circuit-level dissection of behavior in single animals.

neuroscience↗

bioRxiv2023

A small-molecule TrkB ligand improves dendritic spine phenotypes and atypical behaviors in female Rett syndrome mice

Rett syndrome (RTT) is a neurodevelopmental disorder caused by mutations in methyl-CpG-binding protein-2 (MECP2), encoding a transcriptional regulator of many genes, including brain-derived neurotrophic factor (Bdnf). BDNF mRNA and protein levels are lower in RTT autopsy brains and in multiple brain regions of Mecp2-deficient mice, and experimentally increasing BDNF levels improve atypical phenotypes in Mecp2 mutant mice. Due to the low blood-brain barrier permeability of BDNF itself, we tested the effects of a brain penetrant, small molecule ligand of its TrkB receptors. Applied in vitro, LM22A-4 increased dendritic spine density in pyramidal neurons in cultured hippocampal slices from postnatal day (P) 7 male Mecp2 knockout (KO) mice as much as recombinant BDNF, and both effects were prevented by the TrkB receptor inhibitors K-252a and ANA-12. Consistent with its partial agonist activity, LM22A-4 did not affect spine density in CA1 pyramidal neurons in slice cultures from male wildtype (WT) mice, where typical BDNF levels outcompete its binding to TrkB. To identify neurons of known genotypes in the mosaic brain of female Mecp2 heterozygous (HET) mice, we treated 4-6-month-old female MeCP2-GFP WT and HET mice with peripheral injections of LM22A-4 for 4 weeks. Surprisingly, mutant neurons lacking MeCP2-GFP showed dendritic spine volumes comparable to that in WT controls, while MeCP2-GFP-expressing neurons showed larger spines, similar to the phenotype we described in symptomatic male Mecp2 KO mice where all neurons lack MeCP2. Consistent with this non-cell-autonomous mechanism, a 4-week systemic treatment with LM22A-4 had an effect only in MeCP2-GFP-expressing neurons in female Mecp2 HET mice, bringing dendritic spine volumes down to WT control levels, and without affecting spines of MeCP2-GFP-lacking neurons. At the behavioral level, we found that female Mecp2 HET mice engaged in aggressive behaviors significantly more than WT controls, which were reduced to WT levels by a 4-week systemic treatment with LM22A-4. Altogether, these data revealed differences in dendritic spine size and altered behaviors in Mecp2 HET mice, in addition to provide support to the potential usefulness of BDNF-related therapeutic approaches such as the partial TrkB agonist LM22A-4.

neuroscience↗

bioRxiv2023

Hippocampal and amygdala subfield volumes in obsessive-compulsive disorder differ according to medication status.

IntroAlthough it has been suggested that the hippocampus and amygdala (HA) are involved in the neurobiology of obsessive-compulsive disorder (OCD), volumetric findings have been inconsistent. Furthermore, the HA consist of heterogenous anatomic units with specific functions and cytoarchitecture, and little work has been undertaken on the volumetry of these subfields in OCD. MethodsT1-weighted images from 381 patients with OCD and 338 healthy controls (HCs) from the OCD Brain Imaging Consortium were segmented to produce twelve hippocampal subfields and nine amygdala subfields using FreeSurfer 6.0. We assessed between-group differences in subfield volume using a mixed-effects model adjusted for age, quadratic effects of age, sex, site, and whole HA volume. Given evidence of confounding effects of clinical characteristics on brain volumes in OCD, we also performed subgroup analyses to examine subfield volume in relation to comorbid anxiety and depression, medication status, and symptom severity. ResultsPatients with OCD and HCs did not significantly differ in HA subfield volume. However, medicated patients with OCD had significantly smaller hippocampal dentate gyrus (pFDR=0.042, d=-0.26) and molecular layer (pFDR=0.042, d=-0.29) and larger lateral (pFDR=0.049, d=0.23) and basal (pFDR=0.049, d=0.25) amygdala subfields than HCs. Unmedicated patients had significantly smaller hippocampal CA1 (pFDR=0.016, d=-0.28) than HCs. No association was detected between any subfield volume and OCD severity. ConclusionDifferences in HA subfields between OCD and HCs are dependent on medication status, in line with previous work on other brain volumetric alterations in OCD. This emphasizes the importance of considering psychotropic medication in neuroimaging studies of OCD.

neuroscience↗

bioRxiv2020

Distinct Predictive Patterns of Antidepressant Response to Sertraline, Placebo and Bupropion using Pre-Treatment Reward Processing as examined through Functional MRI and Deep Learning: Key Results from the EMBARC Study

ImportanceThe lack of antidepressant-specific biomarkers to inform treatment selection is a key obstacle in the treatment of Major Depressive Disorder. Quantitative measurements of reward processing neural activity with task-based functional magnetic resonance imaging (fMRI) may allow prediction of individual outcomes for specific antidepressants. ObjectiveTo build and validate predictors of individual outcomes for sertraline, bupropion, and placebo using reward processing task-based fMRI, clinical assessments, and deep learning. DesignThis is a secondary analysis of data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a placebo-controlled, double-blind randomized clinical trial. The study ran from July 2011 to December 2015 and this analysis was performed between December 2018 and July 2019. SettingThe EMBARC study was conducted at 4 academic medical centers. ParticipantsA random sample of 296 un-medicated participants meeting DSIM-IV criteria for depression was enrolled. InterventionSubjects were randomized to sertraline or placebo during phase 1. In phase 2, non-responders to placebo were treated with sertraline and non-responders to sertraline were treated with bupropion. Each phase lasted for 8 weeks. Main outcomes and measuresThe primary outcome was the change in the 17-item Hamilton Rating Scale for Depression ({Delta}HAMD) after 8 weeks of treatment. Task-related brain activation measures, computed from pre-treatment reward processing task fMRI, and clinical measurements were used to train deep learning predictive models for each treatment group. ResultsThe current analysis includes 222 participants with complete imaging, clinical, and treatment outcome data (146 female, mean age 16.4 {+/-} 13.4 years). The predictive model for sertraline, trained on 106 participants, achieved an R2 of 35% (95% CI 20-50%, p < 10-3) in predicting {Delta}HAMD and a number-needed-to-treat (NNT) of 4.31 in predicting remission. The placebo model, trained on 116 participants, achieved an R2 of 23% (95% confidence interval of 11-37%, p < 10-3) and an NNT of 2.78. The bupropion model achieved an R2 of 37% (95% CI 12-61%, p < 10-3) and an NNT of 2.35. Reward processing activity in regions such as the medial frontal cortex, insula, and thalamus were important predictors of sertraline outcome, while the anterior cingulate cortex, striatum, insula, and thalamus were important regions for predicting bupropion outcome. These are consistent with previously reported findings, while regions not previously implicated such as the temporal pole and paracentral lobule were also found to be predictive. Conclusions and relevanceThese findings demonstrate the utility of reward processing measurements and deep learning in predicting individual antidepressant outcomes with high accuracy. They also present potential composite biomarkers for these treatments based on neuroimaging and clinical features. Trial registrationClinicalTrials.gov identifier: NCT01407094 KEY POINTSO_ST_ABSQuestionC_ST_ABSCan pre-treatment fMRI measurements of reward processing, in combination with multi-dimensional clinical assessments, be used to form personalized predictions of antidepressant outcomes? FindingsDeep learning predictive models trained on pre-treatment reward processing task-based neuroimaging and clinical data from a randomized clinical trial were able to explain up to 37% of the variance in individual treatment outcomes and predict remission with NNT of 2-4. Specific clinical variables and brain regions with reward processing activity important for the model predictions were identified, which may form composite biomarkers of antidepressant response. MeaningQuantitative measures of reward processing, as identified through deep learning, may move us closer to a precision medicine approach that enables clinicians to select the appropriate antidepressant for each patient with greater certainty.

bioinformatics↗

bioRxiv2018

Ventral hippocampal projections to the medial prefrontal cortex regulate social memory

Inputs from the ventral hippocampus (vHIP) to the medial prefrontal cortex (mPFC) have been implicated in several neuropsychiatric disorders. Here, we show that the long-range vHIP-mPFC projection is hyperactive in the Mecp2 knockout (KO) mouse model of the autism spectrum disorder Rett syndrome, which has deficits in social memory. Chronically mimicking vHIP-mPFC hyperexcitability in wild-type mice impaired social memory, whereas chronic inhibition of mPFC-projecting vHIP neurons in Mecp2 KO mice rescued social memory deficits; the extent of memory rescue was negatively correlated with the strength of vHIP input to the mPFC. Acute manipulations of the vHIP-mPFC projection also affected social memory in a specific and selective manner, suggesting that proper vHIP-mPFC signaling is necessary to recall social memories. In addition, we identified an altered vHIP-mPFC innervation pattern and increased synaptic strength onto layer 5 pyramidal neurons as contributing factors in aberrant vHIP-mPFC signaling in Mecp2 KO mice.

neuroscience↗

bioRxiv2018

Fungal community assembly in soils and roots under plant invasion and nitrogen deposition

Abstract Fungal community composition in the Anthropocene is driven by rapid changes in environmental conditions caused by human activities. This study examines the relative importance of two global change drivers - atmospheric nitrogen (N) deposition and annual grass invasion - on structuring fungal communities in a California chaparral ecosystem, with emphasis on arbuscular mycorrhizal fungi. We used molecular markers, functional groupings, generalized linear statistics and joint distribution modeling, to examine how environmental variables structure taxonomic and functional composition of fungal communities. Invasion of a chaparral ecosystem decreased richness and relative abundance of non-AMF symbionts and rhizophilic AMF (e.g. Glomeraceae) as well as the proportion of edaphophilic AMF (e.g. Gigasporaceae). We found increased richness and the proportion of rhizophilic and edaphophilic AMF with increasing soil NO3. Our findings suggest that invasive persistence may decrease the presence of multiple soil symbionts that native species depend on for pathogen protection and increased access to soil resources.

ecology↗

bioRxiv2017

t-Darpp is an elongated monomer that binds to calcium and is phosphorylated by cyclin-dependent kinases 1 and 5

t-Darpp is a protein encoded by the PPP1R1B gene and is expressed in breast, colon, esophageal, gastric, and prostate cancers, as well as in normal adult brain striatal cells. Overexpression of t-Darpp in cultured cells leads to increased protein kinase A activity and increased phosphorylation of AKT (protein kinase B). In HER2+ breast cancer cells t-Darpp confers resistance to the chemotherapeutic agent trastuzumab. To shed light on t-Darpp function, we studied its secondary structure, oligomerization status, metal-binding properties, and phosphorylation by cyclin dependent kinases 1 and 5. t-Darpp exhibits 12% alpha helix, 29% beta strand, 24% beta turn and 35% random coil structures. t-Darpp binds to calcium, but not to other metals commonly found in biological systems. The T39 site, critical for t-Darpp activation of the AKT signaling pathway, is a substrate for phosphorylation by cyclin-dependent kinase 1 (CDK1) and cyclin-dependent kinase 5 (CDK5). Gel filtration chromatography, sedimentation equilibrium analysis, blue native gel electrophoresis, and glutaraldehyde-mediated crosslinking experiments demonstrate that the majority of t-Darpp exists as a monomer, but forms low levels (< 3%) of hetero-oligomers with its longer isoform Darpp-32. t-Darpp has a large Stokes radius of 4.4 nm relative to its mass of 19 kDa, indicating that it has an elongated structure.

biochemistry↗

bioRxiv2017

The Neuron Specific Formin Delphilin Nucleates Actin Filaments but Does Not Enhance Elongation

The formin Delphilin binds the glutamate receptor, GluR{delta}2, in dendritic spines of Purkinje cells. Both proteins play a role in learning. To understand how Delphilin functions in neurons, we studied the actin assembly properties of this formin. Formins have a conserved formin homology 2 domain, which nucleates and remains associated with the fast growing end of actin filaments, influencing filament growth with input from the adjacent formin homology 1 domain. The strength of nucleation and elongation varies widely across formins. Additionally, most formins have conserved domains that regulate actin assembly through an intramolecular interaction. Delphilin is distinct from other formins in several ways: its expression is limited to Purkinje cells; it lacks autoinhibitory domains; its formin homology 1 domains has minimal proline-rich sequence. We found that Delphilin is an actin nucleator that does not accelerate elongation, although it binds tightly to the barbed end of filaments. In addition, Delphilin exhibits a preference for actin isoforms, which has not been described or systematically studied in other formins. Finally, Delphilin is the first formin studied that is not regulated by intramolecular interactions. We speculate how the activity we observe is consistent with its localization in the small dendritic spines.\n\nAbbreviations: FH1, formin homology 1; FH2, formin homology 2; DID, diaphanous inhibitory domain; DAD, diaphanous autoinhibitory domain; LTD, long term depression; PSD, post synaptic density; PDZ, post synaptic density protein (PSD95), Drosophila disc large tumor suppressor (Dlg1), and zonula occludens-1 protein (zo-1).

biochemistry↗

bioRxiv2017

Harmonization of cortical thickness measurements across scanners and sites

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as \"scanner effects\", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements, across a total of 11 scanners. We propose a set of general tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

neuroscience↗